Towards Viable Intrusion Detection Methods For The Automotive Controller Area Network

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

Abstract

The Controller Area Network (CAN) in cars is critical to their safety and performance and is now regarded as being vulnerable to cyberattack. Recent studies have looked at securing the CAN and at intrusion detection methods so that attacks can be quickly identified. The CAN has qualities that distinguish it from other computer networks, while the nature of car production and usage also provide challenges. Thus attach detection methods employed for other networks lack appropriateness for the CAN. This paper surveys the methods that have been investigated for CAN intrusion detection, and considers their implications in terms of practicability and requirements. Consequent developments that will be needed for implementation and research are suggested.
Original languageEnglish
Title of host publication2nd Computer Science in Cars Symposium - Future Challenges in Artificial Intelligence Security for Autonomous Vehicles (CSCS 2018)
PublisherACM
Number of pages9
ISBN (Print)978-1-4503-6616-8
DOIs
Publication statusPublished - 13 Sep 2018
EventACM Computer Science in Cars Symposium: Future Challenges in Artificial Intelligence & Security for Autonomous Vehicles - Munich, Germany
Duration: 13 Sep 201814 Sep 2018

Conference

ConferenceACM Computer Science in Cars Symposium
Abbreviated titleCSCS 2018
CountryGermany
CityMunich
Period13/09/1814/09/18

Keywords

  • intrusion detection, controller area network, automotive cybersecurity

Fingerprint Dive into the research topics of 'Towards Viable Intrusion Detection Methods For The Automotive Controller Area Network'. Together they form a unique fingerprint.

Cite this